Utility companies in the field of electric power generation are being impacted by deregulation and increasing competition. Thus, cost containment and the ability to generate electricity at the lowest possible cost have become increasingly important issues. Improving efficiencies in the electric power generation process can reduce fuel costs, thereby reducing electricity production costs. To this end, improvements in “heat rate” and thermal performance can result in significant fuel cost savings. As used herein, “heat rate” refers to the number of units of total thermal input (i.e., fuel heat input) required to generate a specific amount of electrical energy (i.e., electrical power output). Heat rate provides a measure of thermal efficiency and is typically expressed in units of Btu/kWh in North America. Fuel heat input can be estimated by multiplying the fuel input flow rate times the fuel heat content. Fuels for electric power generation include, but are not limited to, coal, oil, natural gas and other combustible fuels.
In a conventional fossil fuel-fired (e.g., coal-fired) power plant a fossil fuel/air mixture is ignited in a boiler. Large volumes of water are pumped through tubes inside the boiler, and the intense heat from the burning fuel turns the water in the boiler tubes into high-pressure steam. The high-pressure steam from the boiler passes into a turbine comprised of a plurality of turbine blades. Once the steam hits the turbine blades, it causes the turbine to spin rapidly. The spinning turbine causes a shaft to turn inside a generator, creating an electric potential. A combustion turbine can run on natural gas or low-sulfur fuel oil. Air enters at the front of a turbine and is compressed, mixed with natural gas or oil, and ignited. The hot gas then expands through turbine blades to turn a generator and produce electricity. It should be understood that in some boiler configurations, a portion of the generated steam is re-routed to a heat exchanger or to a process. This re-routed steam does not pass through the turbine.
For boilers, there are two primary types of boiler efficiency optimization. The first is the on-going optimization of operation that is primarily under the direction of an operator through operator-controllable input parameters. The second is the periodic optimization that is under the direction of a performance engineer and a maintenance department. Of these two, the on-going optimization by the operator has the potential for a real-time positive impact on the performance of the steam generation unit.
A neural network optimization system requires a goal that is reliable and repeatable. Reliable meaning that a value is not prone to physical faults in the sensing. Repeatable meaning that a given operating point results in the same output. If the goal is better efficiency, then an efficiency-based value is required that is reliable and repeatable. Efficiency is a calculated value from many different sensor inputs. This calculation may require manual input from the operator. Manual inputs must be updated accurately and in a timely fashion or else the result of the calculation will be erroneous.
Existing performance calculations for utility boilers calculate performance based on many parameters from the boiler, turbine, as well as the balance of the power plant. These existing performance calculations are designed to compute an overall efficiency for conversion of coal or gas, or other fuel input into electricity. Plant operators may use performance calculation results to adjust boiler operation, engineers may use performance calculation results to identify performance problems, and plant management may use performance calculation results as a performance evaluation criteria for the facility.
Commonly, a value for heat rate is determined, and used as a performance indicator for a power plant. Input parameters to the existing heat rate calculations are comprised of two groups of parameters. The first set of parameters can be controlled or altered by operators or control systems (i.e., controllable input parameters). The second set of parameters are outside the immediate control or alteration by operators and control systems (i.e., non-controlled input parameters). The non-controlled input parameters include, but are not limited to, fuel composition/quality, equipment condition, weather conditions, extracted steam or energy, non-fuel additives, non-controlled process pressures and pressure imbalances, non-controlled non-compensated fluid flows, non-controlled back pressures or gas stream restrictions, parameters originated at post-combustion equipment (including, but not limited to, Selective Catalytic Reduction (SCR) systems), Fluidized Gas De-Sulphurization (FGD), heat exchangers, and Electrostatic Precipitator (ESP) parameters), originated at pre-combustion equipment (including, but not limited to, coal blending apparatus and fuel analyzer), instrument signal drift, and non-repeatability of sensor inputs.
Calculations of heat rate can be as simple as making an estimate of the fuel heat input (i.e., fuel input flow rate times fuel heat content) and dividing this by the net electrical power output. Calculations for heat rate can also be as complex as doing full heat balances around an entire power plant, utilizing temperatures, pressures, flows, fuel analysis data, flue gas analysis, ash analysis, ambient air analysis (humidity), etc., while also using the net or gross generator electrical output. The computational procedure varies with the amount of detailed information and instrumentation that is available for a particular boiler.
Heat rate is a measure of end-to-end thermal efficiency (related to the reciprocal of the overall thermal efficiency). Most often, the overall thermal efficiency is broken down into terms of boiler efficiency and turbine/generator efficiency. The boiler efficiency rates how much of the input heat is put into heating water, evaporating water and superheating the steam produced, whereas the turbine/generator efficiency rates how effectively the heat captured by steam is converted into electricity.
A common method in the industry for defining boiler efficiency is the ASME losses method, also known as the “heat loss method.” The heat loss method accounts for various efficiency losses in the boiler on an individual basis. These losses can usually be quantified by observing a limited number of plant operating parameters.
The current problem with calculating an overall heat rate is that inputs can be noisy, or non-repeatable, making it difficult for calculations that are actionable by operators. Even with time averaging or other statistical manipulation, a typical 10 minute average will often have an error band of +/−2%, which is often greater than the improvements operators or control systems can adjust or resolve. In other words, the signal-to-noise (S/N) ratio presents a difficult situation for evaluation.
The long term, effects of non-controlled input parameters, can make it difficult to ascertain if operators are maintaining good practices for heat rate minimization. For automated systems, such as a combustion optimization system (COS) that automatically tune a combustion environment, these data errors exhibit themselves in poor quality models and in a delay time to take action because of a need to await statistical management of problematic data.
The present invention provides a system for determining performance characteristics based on input parameters that are controllable by an operator or control system (e.g., a combustion optimization system) and can affect overall heat rate.